Thursday, 29 November 2012

My previous post didn't have too many useful snippets in it (mainly useful techniques to make your own snippets), and I thought I could improve on that. This post is not a good read in isolation - it's probably a good idea to read my previous post first, if you haven't already.

Tesseral addition (see previous post) was nice, but very often you only need to increment/decrement one dimension of a coordinate (for example when iterating over a portion of a Z-ordered grid in reading order), equivalent to adding/subtracting (1, 0) or (0, 1) to/from a coordinate. Since only one part of the coordinate changes, only about half as much code is necessary. Also, since the thing being added to the coordinate is a constant, one of the masking operations can be merged with it.

Note that the only difference is that the mask and the complemented mask have switched places.

This TesseralMax and the TesseralMin from the previous post can be combined with the increments and decrements (and with full tesseral addition, but that's less frequently useful) to form saturating increments and decrements, useful for sampling around a position on a Z-ordered grid without getting out of bounds.

Merging them this way is nice, because only "half" of a TesseralMin or TesseralMax is necessary that way. On the other hand, they do have the overflow problem again, though that usually won't be a problem.

Tuesday, 27 November 2012

Tesseral arithmetic is a type of arithmetic that operates on interleaved coordinates. That may not seem very useful, so first, when would you want to do that?

The Z-order curve is a space-filling curve (also known as Morton order, Morton coordinates, etc) that is closely related to quad trees (and octrees) and (in some contexts) improves the locality of reference when working with multidimensional data.

In essence, it maps multidimensional coordinates to single-dimensional coordinates, which can be used to address memory, and it does so in a way that sometimes leads to better locality of reference than concatenating the parts of a coordinate into a longer one. The trick is to interleave the bits. While that is not the best (ie. optimal locality of reference) mapping, but it's interesting that it works so well for such a simple trick.

But where it really gets interesting is when you have interleaved coordinates and you want to do math with them. You could unpack them, do your math, and then repack, but if you follow the previous link you can see that while unpacking and packing are simple and fast relative to the mappings of other space-filling curves, unpacking and packing would add a lot of overhead to what would otherwise be simple math.

That's where tesseral arithmetic comes in.

Bitwise AND, OR and XOR still work the same way, because the bits of the result only depend on the corresponding bits in the inputs. Shifts are simple - the shift count must be multiplied by two. So for example x ^ (x << 1) becomes x ^ (x << 2) in tesseral arithmetic.

Addition is more trouble. The carries in normal addition propagate into bits they shouldn't be affecting in tesseral arithmetic. But consider what would happen if the bit pairs at odd positions would each sum to 1. A carry coming into an odd position would always be passed on, and no extra carries would be generated from odd positions. So if the bits at odd positions are just right, the bits at the even positions are summed tesserally, with the carry moving two places instead of one. Obviously this extends to the odd bits as well, when the bits at even positions are just right. This actually makes tesseral addition quite simple:

Unsurprisingly, the same principle applies to subtraction. In subtraction, borrows are passed on unmodified through a pair of bits if they sum to zero, or in other words, if both are zero. In a way that's conceptually even simpler than addition.

But multiplication isn't that nice. The problem is that multiplication is basically build out of a lot of shifts and additions (it's not implemented that way in hardware anymore) and the additions aren't tesseral nor can they be made tesseral.
Unless, of course, we implement multiplication in software:

But that doesn't achieve the goal of being faster than unpacking, doing math, and repacking. If anyone has a better idea, please let me know.

So ok, no tricks multiplication or division. But we're not done. As I hinted in my previous post, many bitwise tricks extend to tesseral arithmetic. For example, taking the absolute value of both parts of the coordinate simultaneously, using the same trick as in my previous post (working with the signbit). The basic principle is simple: replace all operations by their tesseral counterparts. Then look for simplifications and other improvements.

The mask is known to be either all ones or all zeroes. It may seem at first as though that means we'd have to OR it with something to make the "in between" bits sum to one, but when the mask is zero there are no carries to pass on anyway. So the OR can be skipped.

But calculating absolute values of coordinates doesn't happen that often. So let's calculate an element-wise minimum, using the same basic principle as before, replace normal operators by tesseral operators. This time however, a substantial improvement over the non-tesseral version is possible.

And there's something very nice about how that worked out. In the normal min, there was a problem with overflow. That doesn't happen here, because for xdiff there was an extra bit anyway, and for ydiff that extra bit could easily be arranged by shifting right by 1. That makes the comparison unsigned, though, because the "extra bit" is zero, not a sign-extended bit.

So that's it for this post. Many other bitwise tricks can be extended to tesseral math, using the same basic principle. And of course this all generalizes to higher dimensions as well.

In the next post, I'll have some more useful snippets for tesseral arithmetic.

There are some other references for this type of arithmetic or its generalizations, for example The Art of Computer Programming volume 4A which calls this "working with fragmented fields" and Morton-order Matrices Deserve Compilers’ Support which calls this the "algebra of dilated integers".

By the way I originally wrote this post thanks to (or maybe due to?) this article, which I found by searching how to do coordinate arithmetic in a quad tree with Morton order. That's where the title comes from. Unfortunately the article didn't really say how to actually do it, so I worked that out (though the algebra of dilated integers had been explored before, I did not know it went by that name) and posted it for the benefit of other people who perhaps traversed the same steps up to that point.

Sunday, 18 November 2012

this is a filler (in that it is much easier than the usual material), but it seems like most readers only read the fillers anyway

When I write signbit, I mean the upper bit in a bit string that is interpreted as a two's complement signed integer.

Central to working with the signbit is the idea that signed shift right aka arithmetic shift right copies the signbit to other bits, and specifically, a signed shift right by 31 (or 63 or in general, one less than the size of your numbers) broadcasts the signbit to all other bits.

Perhaps the most obvious thing you can do with that is broadcasting an arbitrary bit to all other bits. Simply shift that bit into the signbit, and then shift right by 31:

In C, that's undefined behaviour (UB). Letting a left shift overflow (which could easily happen here) is UB, and signed right shift is UB in any case. But this is C# code (the source of this page will tell you so) where it's perfectly well-defined. And anyway, this is the kind of UB that is safe to use; the expected thing happens when you combine a sane compiler with a typical platform (say, MSVC on x86). But, of course, purists won't like it and on platforms without arithmetic right shift it's probably not going to work.

That actually applies to most of this blog, I suppose.

On to other tricks. This one is slightly harder to grasp, but more useful: calculating the absolute value of an integer without branching. First, the simple to understand version.

The better way to do this has to do with how negation works. The negation of a number x is ~x + 1 (first definition) or ~(x - 1) (second definition). Those definitions are, of course, equivalent. The trick (and you may have seen this coming), is to make the complement and the increment/decrement conditional based on the mask.

I've heard that the version of abs using the first definition is patented. That probably doesn't hold up (there will be a mountain of prior art and it's an obvious trick that anyone could derive), and no one's going to find out you're using it much less sue you for it, but you could use the version using the second definition just to be on the safe side.

One good thing about the simple version of abs is that it's using a generic branchless selection. That means you're not limited to choosing between value and -value, you can select anything. For example, you can subtract two numbers and use the sign of the difference to select the (unsigned) smallest one. That doesn't always work. The subtraction must not overflow, otherwise it selects the wrong one. The problem goes away if the inputs are smaller than ints, for example if they are bytes.

The weird mixing of signed and unsigned may be confusing. Try to think of numbers as pure bit strings and only look at the type when an operator depends on it. That's closer to what actually happens in a computer, and it's less confusing that way.

The problem also goes away if you can use the carry flag instead of the signbit, because then you're not using a bit of the result to hold a flag but a separate thing, and thus doesn't "eat into the range of values". But high level languages are too good for the carry flag or something like that, and don't enable you to use it. So here's min in x86 assembly: